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Unpacking online Learning Experiences: online Learning Self-Efficacy and Learning Satisfactionu

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Internet and Higher Education 19 (2013) 10–17

Contents lists available at ScienceDirect Internet and Higher Education

Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction

Demei Shen a,⁎, Moon-Heum Cho b, Chia-Lin Tsai c, Rose Marra d

a Shanghai Engineering Research Center of Digital Education Equipment, East China Normal University, China b Lifespan Development and Educational Sciences, Kent State University at Stark, United States

c Department of Psychological Sciences, University of Missouri – Columbia, United States

d School of Information Science and Learning Technologies, University of Missouri – Columbia, United States

article info

Article history:

Accepted 8 April 2013 Available online 15 April 2013


Online learning Self-efficacy

Online learning self-efficacy Learning satisfaction

1. Introduction

Beliefs about self-efficacy determine level of motivation as reflected in the amount of effort exerted in an endeavor and the length of time persisting in a difficult situation (Bandura, 1988). Self-efficacy is defined as “people's judgments of their capabilities to organize and execute a course of action required to attain designated types of performances” (Bandura, 1986, p. 391). If a person has a low level of self-efficacy toward a task, he or she is less likely to exert ef- fort; therefore, the person will less likely achieve. Other research find- ings have demonstrated that self-efficacy is a better predictor of academic achievement than any other cognitive or affective processes (Schunk, 1991); therefore, self-efficacy is critical in learning and per- formance (Hodges, 2008).

Student self-efficacy seems particularly important in challenging learning environments, such as an online learning environment where students lack the opportunity to interact with others and as a result can become socially isolated and easily lost (Cho & Jonassen, 2009; Cho, Shen, & Laffey, 2010). Recent studies have shown that the drop-out rate among students in online learning environments is higher than in traditional learning environments (Ali & Leeds, 2009). Some re- searchers have asserted that the drop-out rate is related in part to lack

⁎ Corresponding author. Tel.: +86 1 206 524 3022.

E-mail addresses:, (D. Shen).

1096-7516/$ – see front matter © 2013 Elsevier Inc. All rights reserved.


Self-efficacy is believed to be a key component in successful online learning; however, most existing studies of on- line self-efficacy focus on the computer. Although computer self-efficacy is important in online learning, researchers have generally agreed that online learning entails self-efficacy of multifaceted dimensions; therefore, one of the purposes of the current study was to identify dimensions of online learning self-efficacy. Through exploratory factor analysis, we identified five dimensions of online learning self-efficacy: (a) self-efficacy to complete an online course, (b) self-efficacy to interact socially with classmates, (c) self-efficacy to handle tools in a Course Management System (CMS), (d) self-efficacy to interact with instructors in an online course, and (e) self-efficacy to interact with class- mates for academic purposes. In addition, the role of demographic variables in online learning self-efficacy was in- vestigated. Demographic variables, such as the number of online courses taken, gender, and academic status were found to predict online learning self-efficacy. Furthermore, we found that online learning self-efficacy predicted stu- dents' online learning satisfaction. Results are discussed, and implications for online teaching and learning are provided.

© 2013 Elsevier Inc. All rights reserved.

of self-efficacy (Lee & Choi, 2011). Researchers have argued that with the self-directed nature of online learning, self-efficacy can be a key component of academic success in distance education (Hodges, 2008); therefore, understanding self-efficacy in online learning is critical to im- prove online education. The current study was an investigation of self-efficacy in online learning settings.

2. Self-efficacy in online learning settings

Self-efficacy is context-specific (Bandura, 1986). In terms of online self-efficacy, we need to consider at least three areas: technology, learn- ing, and social interaction; however, a majority of researchers of online self-efficacy consider only the technological aspect of online learning. Consequently, self-efficacy in the other two areas has rarely been explored.

With regard to technology, numerous studies have been conducted on the role of technological self-efficacy in online student achievement. For instance, McGhee (2010) found a significant, moderate, and positive relationship between online technological self-efficacy and the academ- ic achievement of 45 community college students. Thompson and Lynch (2003) studied the psychological processes underlying resistance to web-based instruction (WBI) and demonstrated that students with weak Internet self-efficacy beliefs tended to resist WBI.

Regarding learning, Ergul (2004) showed that self-efficacy in dis- tance education significantly and positively predicted students' academic

achievement. In addition, Artino (2008) found that students with higher self-efficacy for computer-based learning are more likely to experience learning satisfaction than students with low self-efficacy.

In terms of social interaction, Cho and Jonassen (2009) found two di- mensions of online self-efficacy: self-efficacy to interact with instructors and self-efficacy to contribute to the online community. In addition, they found that students who have high self-efficacy in interacting with in- structors and contributing to the online community are more likely to use active interaction strategies, such as writing, responding, and reflecting. According to Cho and Jonassen researchers of online learning self-efficacy should consider diverse situations that can occur in online learning



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